Field of the Invention
The present invention concerns a method for magnetic resonance imaging using prospective motion correction and a corresponding magnetic resonance system.
Description of the Prior Art
In magnetic resonance (MR) imaging, an MR image is produced which maps a region of interest. A certain period of time (scan time) is typically required for obtaining the MR data. It may happen that an object being scanned moves during the scan time. This motion often reduces the MR image quality. For example, motion artifacts occur.
Techniques for reducing motion artifacts (motion correction) are well known. Motion correction is often also termed motion compensation. Reduction can mean complete or partial elimination of the motion artifacts. In particular, so-called prospective motion corrections are known. Here information about the motion is obtained even during MR data acquisition (scanning) and this information is used for motion correction as scanning proceeds. Parameters of a scan sequence are typically adjusted such that the motion is counteracted.
Prospective motion correction can be differentiated from retrospective motion correction, for example, in which motion correction is carried out when scanning is complete, which means that the parameters of the scan sequence can no longer be adjusted.
Purely retrospective techniques suffer from an inherently limited motion correction accuracy; no prospective adjustment of the scan sequence parameters is possible. As a result, it may occur that certain information is basically not obtained and has to be reconstructed by particular model assumptions or interpolated. This can result in distortions. Moreover, such techniques require significant computing capacities.
Techniques are also known, for example, in which so-called navigator scans are slotted in during the scan time and allow prospective motion correction, see e.g. A. van der Kouwe et al., “Real-time rigid body motion correction and shimming using cloverleaf navigators” in Magn. Reson. Med. 56 (2006) 1019-1032 or M. D. Tisdall et al., “Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI” in Magn. Reson. Med 68 (2012) 389-399. Additional navigator images are sampled in order to detect and correct the motion. In addition, the motion is typically modeled by an extended Kalman filter for state change, see e.g. N. White et al., “PROMO: Real-time prospective motion correction in MRI using image-based tracking” in Magn. Reson. Med 63 (2010) 91-105. The use of navigators can increase scan sequence complexity. Thus it may be necessary to adjust the chronological order of the scan sequence such that the navigators can be slotted in.
Prospective motion correction techniques based on external camera systems are also known. The motion can be detected by a camera system. However, this typically requires a considerable hardware overhead, see e.g. M. Zaitsev et al., “Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system.” in Neuroimage 31 (2006) 1038-1050. In addition, the hardware components used must be capable of operating even in the powerful main magnetic field of the MR system and should not cause artifacts due to abrupt susceptibility changes, for example.
Prospective motion correction in conjunction with so-called functional MR imaging (fMRI), for example, is known. For fMRI, a time series of volumetric MR images is generated and the change in MR image intensity caused therein by a blood-oxygen-level-dependent (BOLD) change in blood flow is examined (BOLD contrast). During the scan, the patient performs a wide range of tasks, known as paradigms, for selectively activating individual brain areas, such as observing a visual stimulus—e.g. flickering chessboard pattern, emotive pictures —, motor tasks—e.g. finger tapping—, through to perceiving acoustic stimuli. Statistical analysis of the correlation between the change in the BOLD contrast in the MR images generated and the simultaneously performed paradigms provides the activation of the respective areas of the brain in the form of statistical result cards.
Even relatively small movements, particularly head movements, e.g. in the order of millimeters, as can occur during the measurement of neurofunctional images with fMRI, can result in significant motion artifacts and impairments of the statistical result cards generated. Physiological information may be lost as a result.
In order to correct patient movement, prospective motion corrections and/or retrospective motion corrections can be used. Particularly in the case of fMRI, motion correction constitutes a central part of image processing, enabling the detected activation and therefore conformance to the paradigm to be increased by up to 20% and the size of the activation area up to 100%, see e.g. T. R. Oakes, et al. “Comparison of fMRI motion correction software tools.” in Neuroimage 28 (2005) 529-543. In this connection, techniques are known, for example, in which, based on an MR image of the time series of MR images, motion correction parameters are generated for subsequently acquired MR data for another MR image. For which, see S. Thesen et al., “Prospective Acquisition Correction for Head Motion With Image-Based Tracking for Real-Time fMRI” in Magn. Reson. Med. 44 (2000) 457-465, where FIG. 1 shows that the MR image (n+1) is measured using prospective motion correction based on motion correction parameters of the measurement of the MR image (n). For this purpose the MR data of the MR image (n+1) is registered onto reference MR data.
However, such an approach has certain disadvantages and limitations. For example, significant patient motion may already occur during the scan time for one or more MR images. It is then impossible, or only possible to a limited extent, to determine motion correction parameters for a subsequently acquired MR image. In particular, it can be possible that no unambiguous transformation for determining the motion correction parameters can be ascertained.